Reading to Do a Task Outside the Website Now

Readers who interact with a website to do a task outside the website seek to complete their task while reading the website for the information they need. Examples of such websites include sites that describe how to repair a household appliance or how to cook a meal. The figure shows the interaction between the readers’ goal and their interaction with the content.

Reading to do a task outside of the website now

In this type of interaction, readers interact with the content after they decide to perform the task and end their interaction with the content when they feel confident enough to complete the task without additional information. At that point, they continue towards their goal without the content. Depending on the complexity and duration of the task, readers might return to the content several times during the task, but the key aspect of this interaction with the content is that it does not coincide with task completion.

This interaction can influence several aspects of the design. For example, readers might like to print the web content to save or refer to later, so it might be inconvenient to have the web content spread over several web pages. However, because readers might stop interacting with the content at any point, the content could be divided into individual pages of logical steps with natural breaks.

Because readers stop interacting with the content before the complete their task, asking for information about their task when they leave the content might be confusing because they haven’t finished it, yet. On the other hand, asking about the content might be reasonable.

Tracking progress, success, and satisfaction for this type of interaction requires coordination with the content design. The task and subtask flows must be modeled in the content’s design so that the instrumentation used to collect data about the interaction coordinates with the readers’ interaction. Because readers can leave the content before they read all of the content and still complete their task successfully, traditional web-based metrics such as average time-on-page and path are ambiguous with respect to the readers’ experiences. It is impossible, for example, to know if having readers exit a procedure on the first step is good or bad without knowing whether they are also dissatisfied or unsuccessful with the content. Ideally, collecting information about their experience will come shortly after they accomplish their goal. For example, posting a review of their recipe on social media after they finish.

Reading to be Reminded

Reading to be reminded, or Reading to Do Lite, occurs when readers visit an informational site with the confidence that they already know most of what they need to know about a topic to complete their task, but they just need a refresher. Readers use the website as a form of offline information storage that they may use either online or elsewhere. By knowing the information is available online, readers are confident that they don’t need to remember the details, just where they can find them. Brandt et al. [1] noticed this pattern while observing software developers who “delegated their memory to the Web, spending tens of seconds to remind themselves of syntactic details of a concept they new [sic] well.”

The figure shows how interactions of this type might relate to a reader’s task.

Reading to be reminded

Because, as Redish [2] says, readers will read “until they’ve met their need,” readers will spend as little time in the site as they need interacting with the content. Once they have been reminded of the information they need, they will return to their original task.

Topic design principles needed to serve this interaction include making the content easy to find, navigate, and read. Visible headings and short “bites” and “snacks” of information [2] are well suited to such a goal. However, my research in developer documentation says that these guidelines depend on the specific context–a reminder to know your audience. Knowing your audience is also key to using the terms they will recognize.

Website-based metrics are not particularly helpful in determining the quality of the readers’ interactions. A good time-on-page value, for example, might be short–to the point of appearing to be a bounce, or it might be long. The number of times a page is viewed also has an ambiguous meaning when it comes to understanding the quality of the readers’ interactions.

At the same time, the readers’ engagement and focus on their primary task (the one that sent them to this content) means asking qualitative information about their experience is likely to be seen as a distraction. Asking about the reader’s experience should be done soon after the interaction and with as brief of a satisfaction questionnaire as possible—perhaps only one question, such as “Did this topic help you?”

Reading to Do Here

Reading to accomplish a task in the website, or Reading to Do Here, is characterized by readers interacting with a page in a website to accomplish a specific task through the site. In this interaction, the readers’ goal is to complete the task in the web site. Some familiar examples might include registering for a library account, subscribing to an online newsletter, or renewing a business license.

Readers interact with the content or the site shortly after they decide to accomplish the task and they leave shortly after they finish. The figure illustrates the interaction in such a task.

Reading to Do Here

Readers who use content in this way will want to find the page to help them accomplish the task as quickly as possible and then complete the task as efficiently as possible. While they will want to know that they have successfully completed the task before they leave the website, after they leave the website, they generally won’t remember much about the experience unless it was especially negative or positive.

The figure shows a very common type of web interaction. Web usability guidelines describe the design implications that depend on the site, context, and audience in many texts. Because the readers’ task is performed almost entirely in the context of the web interaction, measuring the success of the interaction is easily accomplished through the site without imposing on the reader. The web server can collect data concerning the time spent in the interaction; the rate of successful operations (e.g., registrations, applications, or whatever the interaction is designed to accomplish); and the path through the interaction (e.g., back tracks, sidetracks, and early exits). Requests for qualitative feedback should occur soon after the interaction so readers’ remember the interaction. While this interaction model is intended for informational sites, it also matches the interaction model of commercial sites, such as shopping or other e-commerce sites. As such, many of the analytics tools and instruments that work in those contexts will also work in this interaction model.

That measuring API documentation is difficult is one of the things I’ve learned from writing developer docs for more than 11 years. Running the study for my dissertation gave me a detailed insight as to some of the reasons for this.

The first challenge to overcome is answering the question, “What do you want to measure?” A question that is followed immediately by, “…and under what conditions?” Valid and essential, but not simple, questions. Stepping back from that question, and a higher-level question comes into view, “What’s the goal?” …of the topic? …of the content set? and then back to the original question, of the measurement?

For my dissertation, I spent considerable effort scoping the experiment down to something manageable, measurable, and meaningful–ending up at the relevance decision. Clearly there is more to the API documentation experience than just deciding if a topic is relevant, but that’s a pivotal moment in the content experience. The relevance decision also seemed to be the most easily identifiable, discrete event that I could identify in the overall API reference topic experience. It’s a pivotal point in the experience, but by no mean the only one.

The processing model I used was based on the TRACE model presented by Rouet (2006). Similar cognitive-processing models were also identified in other API documentation and software development research papers. In this model, the experiment focuses on step 6.

Even in this context, my experiment studies a very small part of the overall cognitive processing of a document and an even smaller part of the overall task of information gathering to solve a larger problem or to answer a specific question.

To wrap this up by returning to the original question, that is…what was the question?

The goal of the topic is to provide information that can be easily accessible to the reader.

The easily accessible goal is measured by the time it takes for the reader to identify whether the topic provides the information they seek or not.

The experiment simulates the readers task by providing the test participants with programming scenarios in which to evaluate the topics

The topics being studied are varied randomly to reduce order effects and bias and participants see only one version of the topics to bias their experience by seeing other variations.

In this experiment, other elements of the TRACE model are managed by or excluded from the task.

A couple of days ago, I fired up my trusty Garmin GPS-III Pilot to take on a ham-radio trip. After it initialized and found itself, it declared the date to be Dec 2, 1995. I let it sit for a while, thinking that it might just be slow in waking up. After several hours, however, it remained convinced that Christmas 1995 was only just a few weeks away. I had another GPS (or 6) to use, so grabbed another one for the trip and I didn’t get a chance to investigate this temporal lapse until this morning.

It turns out, that this flashback was the result of a date-rollover error. Basically, the GPS uses a 10-bit number to count the number of weeks since January 6, 1980, when time began for GPS units. With 10 binary bits, you can represent 1,024 different things–weeks, in this case. After 1,024 weeks, after the GPS’ calendar returns to the beginning, back in 1980. This occurred in Aug, 1999, but was easily anticipated and GPS units manufactured shortly before that date could be programmed to accommodate the event by correcting for values that would result in a date that predated its manufacture. But, it seems that my GPS has lived long enough for that correction to no longer work as it did 15 years ago (i.e. the corrections to the current week values result in a date that’s reasonable to the GPS: 1995).

It turns out that many vintage GPS receivers manufactured in the mid to late 90s have similar problem, so it’s one that’s easily fixed by using a program written to update even older GPS units in preparation for the 1999 event. After running this program, my GPS-III Pilot is now living in the 21st century and is enjoying a morning in the sun on the back deck as it catches up with what’s been going on in GPS circles recently (i.e. it’s downloading the current satellite information from the GPS satellites).

This is interesting in that it’s a reminder of how even well designed software can surprise you, and it makes me wonder why I’m so attached to a GPS unit that’s almost 20 years old. It could be because we have had a lot of adventures together or it could be that I’m just a pack rat. Either way, we’re both sync’d up to the correct time.

I went to the UX Careers 2015 panel last night to hear about the future of User Experience from a panel of UX veterans. There were about 200 people in attendance to hear about the future of the career. The panel had a mix of in-house and agency UX perspectives, which provided interesting answers to the questions presented by the host.

About half the discussion was about job hunting–what to do/not do in an interview. How to stand out from the [ever growing] crowd. How it’s a “job-seeker’s” market, yet the need for UX researchers is likely to start diminishing. While the answers seemed to be all over the map, more than one panelist remarked that there are many different contexts in which UX research & design are applied and that one-size is not likely to fit all.

The career guidance could best be summarized as: be yourself, know yourself, present yourself with confidence, and find the best fit for you.

The other half of the discussion was about UX trends–the most interesting question to me being, “What’s the next big thing in UX?” (or something to that effect). First off, there is no “next big thing,” just an ongoing evolution of little things and the same old thing (e.g. research and design methods) applied to different stuff. One point that was made, which resonated with my post about the Internet of things, was how the focus should be on the human experience (human-human interaction) more than the human-machine interaction/experience. The notion of invisible experiences and transparent processes was also mentioned.

It was exciting to hear that the future of the best user interface is no user interface. Now that’s a user interface I’ll be able to sketch even with my horrid drawing skills. Of course the user experience of that invisible user interface will still take some [considerable amount of research and] work to design, but at least the UI will finally be easy to sketch.

My blog vision is coming together. Shortly after my last update to the vision document, I realized I had another goal to add:

Limit blog posts to 500 words or less in size (about a 2-minute reading experience)

I’ve been aiming for this since the beginning–my intent being to keep each post succinct for the reader and force me to focus. As a result, I have a few posts still in the unpublished, draft state because they don’t meet that goal, but it’s been good practice.

In reviewing the earlier iterations of the blog vision, there seems to be some unarticulated elements. For example, the first goal was to generate content, but I’ve not set as a goal, develop an audience. While I do, eventually, want to develop an audience, my feeling is that I’ll need some set of content before promoting to an audience will be productive. So, the goal for this year is to accumulate that content. Next year, I might add “attract an audience” as a goal, but I don’t think I’m ready for that, yet.

The question that presents for this exercise is, should my long-term goal of developing an audience be included somewhere in the current vision document? That could be seen as a guiding, long-term goal, or a short-term distraction. As a long-term goal, it would help guide short-term decisions. At the same time, if having that in front of me might attract me to start trying to attract an audience before I have enough content to make it worth their while to stay–making it even harder to win them back, later.

Tracy Rolling wrote a detailed, first-person, customer experience report in Medium about the limitations of activity tracking. It’s not that we can’t track activities, but that the resulting information is something less than useful to the average (read, non-fanatic) consumer. In her article, she describes how her activity tracker can log all manner of data, but it really doesn’t provide much in the way of information that’s useful to her on a daily basis. Consequently, it should come as no surprise that activity trackers are abandoned after just a short period. Her article highlights the value of the end-to-end customer experience.

Looking in from the outside (I don’t own an activity tracker), I don’t know that this fall into disuse is because the tracker puts itself out of a job (saying, in effect, “You’ve achieved your goal! Congratulations. My work is done.”) or it just doesn’t live up to its promise, whatever that was at the time it was bought. In either case, it highlights what seems to be an inherent challenge that the Internet-of-things hasn’t overcome: providing a durable customer value.

In spite of the recent hype, tracking things isn’t new. I’ve been connecting things to devices and vice versa for 35 years. Connecting them to the Internet is new, but recording telemetry is not. The fact that every person in the civilized world is carrying a powerful computer (usually in the shape of a telephone) is a recent phenomena, that one would think holds some promise. However, without a need (be it present or latent), connecting monitoring transducers to a smartphone or the Internet still seems like it’s in the solution-looking-for-a-problem phase of technology.

It’s not unlike the early days of cell phones or PCs–when the technology was a solution in search of a problem. Eventually, problems will be identified (or invented) and then connected with solutions. However, in the meantime, there’s much to learn about both.

Last month, I published a summary of my dissertation study and I wanted to summarize some of the thoughts that the study results provoked. My first thought was that my experiment was broken. I had four distinctly different versions of each topic yet saw no significant difference between them in the time participants took to determine the relevance of the topic to the task scenario. Based on all the literature about how people read on the web and the importance of headings and in-page navigation cues in web documents, I expected to see at least some difference. But, no.

The other finding that surprised me was the average length of time that participants spent evaluating the topics. Whether the topic was relevant or not, participants reviewed a topic for an average of about 44 seconds before they decided its relevance. This was interesting for several reasons.

The average time spend reading a reference topic to determine its relevance in my study was the same whether the topic was relevant to the scenario or not. I would have expected them to be different–the non-relevant topics taking longer than the relevant ones on the assumption that readers would spend more time looking for an answer. But no. They seemed to take about 44 seconds to decide whether the topic would apply or not in both cases.

While, these findings are interesting, and bear further investigation, they point out the importance of readers’ contexts and tasks when considering page content and design. In this case, changing one aspect of a document’s design can improve one metric (e.g. information details and decision speed) at the cost of degrading others (credibility and appearance).

The challenges then become:

Finding ways to understand the audience and their tasks better to know what’s important to them

Finding ways to measure the success of the content in helping accomplishing those tasks

My vision document is still a work in progress, but this is definitely a goal that fits within the vision and principles and is SMART.

I still have more things to consider. The biggest elephant in the room is the portfolio that I’ve managed to avoid for, well, for the past 35 years. Likewise, I want to add more CV material, etc. to tell more about me, but I need to keep the Achievable and Realistic elements of the SMART mnemonic in mind, while not ignoring the Timely one.

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About the photo

This is a brown pelican that I watched while visiting the beach at Hilton Head Island, S.C. in Summer 2016. Pelicans fascinate me and I can't help but think that they enjoy gliding over the waves at least as much as i enjoy watching them.

For the photo geeks, I took this photo on June 19, 2016 using a Nikon 200-500 f5.6 zoom lens at 420mm at 1/1250 sec on my Nikon D7000 camera. The image was cooled down in Lightroom to give it a bluer-than-natural look for this web site.